calculate

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnly, non-destructive, and idempotent behavior. The description adds that it returns per-timepoint results plus a summary, but does not elaborate on error handling, performance, or data source requirements. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is two sentences: first defines the core functionality, second provides practical use cases. Every word is informative, no fluff or repetition. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description mentions the return value (per-timepoint result + summary), it omits details about return format, error states, missing data handling, or prerequisites (e.g., do indicators need to be from the same entity?). For a tool with 5 parameters and no output schema, the description is adequate but not fully comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is low (20%), with only the 'op' parameter having a description. The description compensates by explaining the operations and their meanings, but fails to detail the 'a', 'b', 'entity', and 'time' parameters (e.g., what format or constraints apply).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool creates derived series from two indicators using specific Excel-style operations (ratio, ratio_pct, diff, sum, product). It provides concrete examples like debt-to-GDP ratio, distinguishing it from sibling tools that focus on comparison, correlation, or data management.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit use cases ('Use for things like...'), providing clear context for when to apply the tool. However, it does not mention when not to use it or highlight alternatives among the many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.